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Operations Research, Management Science, and Industrial Engineering

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[Stanford University]

 

- Operations Research

Operations Research (OR) is a discipline that deals with applying advanced analytical methods to help make better decisions. OR is generally considered a subfield of mathematical sciences. 

Disciplines similar to or overlapping with OR include statistical analysis, management science, game theory, optimization theory, artificial intelligence (AI), and network analysis. The goal of all these techniques is to solve complex problems and improve quantitative decision-making. 

The OR field offers more powerful decision-making methods than ordinary software and data analysis tools. Hiring OR professionals can help companies obtain a more complete data set, consider all available options, predict all possible outcomes, and estimate risk. 

Additionally, OR can be tailored to a specific business process or use case to determine which technologies are best suited to solve the problem.

 

- Operations Research and Analytics

Operations research (OR) and analytics enable organizations to turn complex challenges into enormous opportunities. They turn data into information and information into insights for better decisions and improved outcomes.

OR is a discipline that deals with the development and application of advanced analytical methods to improve decision-making. It is sometimes considered to be a subfield of mathematical sciences. The term management science is occasionally used as a synonym. 

Employing techniques from other mathematical sciences, such as modeling, statistics, and optimization, OR arrives at optimal or near-optimal solutions to complex decision-making problems. 

Because of its emphasis on practical applications, OR has overlap with many other disciplines, notably industrial engineering. OR is often concerned with determining the extreme values of some real-world objective: the maximum (of profit, performance, or yield) or minimum (of loss, risk, or cost). 

Originating in military efforts before World War II, its techniques have grown to concern problems in a variety of industries.

  

- Management Science

In 1967, Stafford Beer described the field of management science as "the commercial use of operations research (OR)". Like OR itself, management science is an interdisciplinary branch of applied mathematics dedicated to optimizing decision planning, with strong links to economics, business, engineering, and other sciences. 

It uses a variety of scientific research-based principles, strategies, and analytical methods, including mathematical modeling, statistical, and numerical algorithms, to improve organizational development by finding optimal or near-optimal solutions to complex decision-making problems. Management scientists use the scientific method of operations research to help businesses achieve their goals. 

The task of management scientists is to use rational, systematic, science-based techniques to inform and improve decisions of all kinds. Of course, the techniques of management science are not limited to commercial applications, but can also be applied to military, medical, public administration, charitable, political, or community groups. 

Management science is concerned with developing and applying models and concepts that may help clarify and solve management problems, as well as design and develop new and better models of organizational excellence. The application of these models in the corporate sector is known as management science.

 

- Artificial Intelligence (AI) and Management Science

Management science is the broad, interdisciplinary study of decision-making and problem-solving within organizations. Interdisciplinary research has strong links with the fields of economics, engineering, management, business administration and more. 

Various scientific principles such as mathematical models, algorithms and statistics are implemented. The goal is to increase and improve the company's capital and make more precise and rational decisions. Management science helps organizations use scientific principles and methods to achieve their goals.

Today, the need for digitalization of enterprises and the use of solutions based on AI are increasingly prominent. The use of smart systems in organizations is not strictly a technical issue, but is also important in the management of modern enterprises.

AI is reshaping the research philosophy and methodology of management science. 

  

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[New York City, Manhattan, New York - Civil Engineering Discoveries]

- Industrial and Systems Engineering

Industrial engineering is an engineering profession that optimizes complex processes, systems or organizations by developing, improving and implementing integrated systems of people, money, knowledge, information and equipment. Industrial engineering is at the heart of the manufacturing business. 

Industrial engineers use specialized knowledge and skills in mathematics, physics, and social sciences, as well as principles and methods of engineering analysis and design, to specify, predict​​, and evaluate outcomes from systems and processes. 

Systems engineering is an interdisciplinary and integrative approach that uses systems principles and concepts and scientific, technical and managerial approaches to enable the successful implementation, use and decommissioning of engineered systems. 

The goal of all systems engineering activities is to manage risk, including the risk of not being able to deliver what the customer wants and needs, the risk of late delivery, the risk of excess costs, and the risk of negative unintended consequences. One measure of the utility of systems engineering activities is the degree to which such risks are reduced. Conversely, the measure of acceptability that systems engineering activities are missing is the resulting level of excess risk.

 

- Industrial Engineering and Smart Manufacturing

Industrial Engineering is an engineering profession that optimizes complex processes, systems or organizations by developing, improving and implementing integrated systems of people, money, knowledge, information and equipment. Industrial engineering is at the heart of the manufacturing business.

Industrial engineers use specialized knowledge and skills in mathematics, physics, and social sciences, as well as principles and methods of engineering analysis and design, to specify, predict, and evaluate outcomes from systems and processes.

Smart manufacturing is the use of interconnected machines and tools to improve manufacturing performance and optimize the energy and labor required to implement big data processing, artificial intelligence and advanced robotics and their interconnection.

  

 

[More to come ...]

 

 

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